Triple
T5938487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attari–Wagah border |
E132104
|
entity |
| Predicate | distanceFromLahore |
P46963
|
FINISHED |
| Object | about 24 kilometres |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: about 24 kilometres | Statement: [Attari–Wagah border, distanceFromLahore, about 24 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromLahore Context triple: [Attari–Wagah border, distanceFromLahore, about 24 kilometres]
-
A.
distanceToLahore_km
chosen
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Lahore.
-
B.
distanceFromKarachi
Indicates the measured spatial distance between a given entity’s location and the city of Karachi.
-
C.
distanceFromIslamabad
Indicates the spatial distance between a given location and the city of Islamabad.
-
D.
distanceFrom Peshawar
Indicates the spatial distance between a given location or entity and the city of Peshawar.
-
E.
directionFromLahore
Indicates the cardinal or relative direction in which one entity is located from Lahore.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c0085c55dc8190aa90e242c956e2fa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03f26f51881908cc253fe5775a1fc |
completed | March 22, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69c03355caf08190b960563a1aed23f9 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:01 p.m.